--- title: "{{< iconify ph clipboard-text >}} Performance" format: html --- ```{r} #| include: false library (dashboardr)``` ```{r, echo=FALSE} dashboardr::enable_modals() ``` ```{r setup} #| echo: false #| warning: false #| message: false #| error: false #| results: 'hide' # Load required libraries library(dashboardr) library(dplyr) library(highcharter) # Global chunk options knitr::opts_chunk$set( echo = FALSE, warning = FALSE, message = FALSE, error = FALSE, fig.width = 12, fig.height = 8, dpi = 300 ) # Load data from dataset_4014obs.rds data <- readRDS('dataset_4014obs.rds') # Data summary cat('Dataset loaded:', nrow(data), 'rows,', ncol(data), 'columns\n') # Create filtered datasets # Each filter is applied once and reused across visualizations data_filtered_984a0efe <- data %>% dplyr::filter(wave == 1) data_filtered_4af682fd <- data %>% dplyr::filter(wave == 2) ``` ```{r, echo=FALSE, message=FALSE, warning=FALSE, results='asis'} # Use dashboardr's loading overlay function dashboardr::add_loading_overlay("Loading", 1, theme = "light") ``` ```{r, echo=FALSE, results='asis'} cat(as.character(dashboardr::modal_content( modal_id = 'PDCCS1R', text = '<h2>Digital Content Creation: Performance Questions</h2> <img src="https://placehold.co/600x400/EEE/31343C" style="max-width:100%; height:auto;"> <p>Information literacy scores were highest at 85%. Participants excelled at search strategies and source evaluation.</p>' ))) ``` ## {{< iconify ph wallet-fill >}} Transactional ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Performance tasks: proportion correct or selected. Where items are multi-select, we show the share selecting each action.", preset = "question") ``` [ {{< iconify ph cards >}} See all Transactional results ](transactional.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-trans-wave1-overall} # Identify trust/safety icon (webshop) result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PTS1R), title = "Identify trust/safety icon (webshop)", questions = "PTS1R", question_labels = "Identify trust/safety icon (webshop)", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave1-age-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PTS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave1-gender-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PTS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave1-edu-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PTS1R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-trans-wave2-overall} # Identify trust/safety icon (webshop) result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PTS1R), title = "Identify trust/safety icon (webshop)", questions = "PTS1R", question_labels = "Identify trust/safety icon (webshop)", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave2-age-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PTS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave2-gender-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PTS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-wave2-edu-item1} # Identify trust/safety icon (webshop) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PTS1R), title = "Identify trust/safety icon (webshop)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PTS1R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-overtime-overall-item1} # Identify trust/safety icon (webshop) result <- create_timeline( data = data, title = "Identify trust/safety icon (webshop)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PTS1R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-overtime-age-item1} # Identify trust/safety icon (webshop) result <- create_timeline( data = data, title = "Identify trust/safety icon (webshop)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PTS1R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-overtime-gender-item1} # Identify trust/safety icon (webshop) result <- create_timeline( data = data, title = "Identify trust/safety icon (webshop)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PTS1R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-trans-overtime-edu-item1} # Identify trust/safety icon (webshop) result <- create_timeline( data = data, title = "Identify trust/safety icon (webshop)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PTS1R", group_var = "Education" ) result ``` ## {{< iconify ph robot-fill >}} AI ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Look closely at the pictures below. Which picture is not made with artificial intelligence (AI)?", preset = "question") ``` [ {{< iconify ph cards >}} See all AI results ](ai.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-ai-wave1-overall} # result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PAIS2_1, PAIS2_2, PAIS2_3, PAIS2_4, PAIS2_5, PAIS2_6, PAIS2_7, PAIS2_8, PAIS2_9), title = "", questions = c("PAIS2_1", "PAIS2_2", "PAIS2_3", "PAIS2_4", "PAIS2_5", "PAIS2_6", "PAIS2_7", "PAIS2_8", "PAIS2_9"), question_labels = c("Google", "Netflix", "Whatsapp", "Facebook", "Bol.com", "DigID", "NOS News", "Albert Heijn", "TikTok"), stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave1-age-item1} # Google result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave1-age-item2} # Netflix result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave1-age-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave1-age-item4} # Facebook result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave1-age-item5} # Bol.com result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave1-age-item6} # DigID result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave1-age-item7} # NOS News result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave1-age-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave1-age-item9} # TikTok result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_9" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave1-gender-item1} # Google result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave1-gender-item2} # Netflix result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave1-gender-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave1-gender-item4} # Facebook result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave1-gender-item5} # Bol.com result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave1-gender-item6} # DigID result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave1-gender-item7} # NOS News result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave1-gender-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave1-gender-item9} # TikTok result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_9" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave1-edu-item1} # Google result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave1-edu-item2} # Netflix result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave1-edu-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave1-edu-item4} # Facebook result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave1-edu-item5} # Bol.com result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave1-edu-item6} # DigID result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave1-edu-item7} # NOS News result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave1-edu-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave1-edu-item9} # TikTok result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_9" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-ai-wave2-overall} # result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PAIS2_1, PAIS2_2, PAIS2_3, PAIS2_4, PAIS2_5, PAIS2_6, PAIS2_7, PAIS2_8, PAIS2_9), title = "", questions = c("PAIS2_1", "PAIS2_2", "PAIS2_3", "PAIS2_4", "PAIS2_5", "PAIS2_6", "PAIS2_7", "PAIS2_8", "PAIS2_9"), question_labels = c("Google", "Netflix", "Whatsapp", "Facebook", "Bol.com", "DigID", "NOS News", "Albert Heijn", "TikTok"), stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave2-age-item1} # Google result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave2-age-item2} # Netflix result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave2-age-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave2-age-item4} # Facebook result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave2-age-item5} # Bol.com result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave2-age-item6} # DigID result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave2-age-item7} # NOS News result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave2-age-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave2-age-item9} # TikTok result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS2_9" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave2-gender-item1} # Google result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave2-gender-item2} # Netflix result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave2-gender-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave2-gender-item4} # Facebook result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave2-gender-item5} # Bol.com result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave2-gender-item6} # DigID result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave2-gender-item7} # NOS News result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave2-gender-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave2-gender-item9} # TikTok result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS2_9" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-wave2-edu-item1} # Google result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_1), title = "Google", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-wave2-edu-item2} # Netflix result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_2), title = "Netflix", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-wave2-edu-item3} # Whatsapp result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_3), title = "Whatsapp", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-wave2-edu-item4} # Facebook result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_4), title = "Facebook", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-wave2-edu-item5} # Bol.com result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_5), title = "Bol.com", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-wave2-edu-item6} # DigID result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_6), title = "DigID", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-wave2-edu-item7} # NOS News result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_7), title = "NOS News", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-wave2-edu-item8} # Albert Heijn result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_8), title = "Albert Heijn", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-wave2-edu-item9} # TikTok result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS2_9), title = "TikTok", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Not selected", "Selected"), stack_map_values = list("1" = "Selected", "0" = "Not selected"), stack_order = c("Not selected", "Selected"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS2_9" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-overtime-overall-item1} # Google result <- create_timeline( data = data, title = "Google", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_1" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-overtime-overall-item2} # Netflix result <- create_timeline( data = data, title = "Netflix", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_2" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-overtime-overall-item3} # Whatsapp result <- create_timeline( data = data, title = "Whatsapp", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_3" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-overtime-overall-item4} # Facebook result <- create_timeline( data = data, title = "Facebook", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_4" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-overtime-overall-item5} # Bol.com result <- create_timeline( data = data, title = "Bol.com", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_5" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-overtime-overall-item6} # DigID result <- create_timeline( data = data, title = "DigID", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_6" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-overtime-overall-item7} # NOS News result <- create_timeline( data = data, title = "NOS News", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_7" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-overtime-overall-item8} # Albert Heijn result <- create_timeline( data = data, title = "Albert Heijn", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_8" ) result ``` ###### item9 ```{r perf-ai-overtime-overall-item9} # TikTok result <- create_timeline( data = data, title = "TikTok", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS2_9" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-overtime-age-item1} # Google result <- create_timeline( data = data, title = "Google", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_1", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-overtime-age-item2} # Netflix result <- create_timeline( data = data, title = "Netflix", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_2", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-overtime-age-item3} # Whatsapp result <- create_timeline( data = data, title = "Whatsapp", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_3", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-overtime-age-item4} # Facebook result <- create_timeline( data = data, title = "Facebook", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_4", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-overtime-age-item5} # Bol.com result <- create_timeline( data = data, title = "Bol.com", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_5", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-overtime-age-item6} # DigID result <- create_timeline( data = data, title = "DigID", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_6", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-overtime-age-item7} # NOS News result <- create_timeline( data = data, title = "NOS News", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_7", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-overtime-age-item8} # Albert Heijn result <- create_timeline( data = data, title = "Albert Heijn", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_8", group_var = "AgeGroup" ) result ``` ###### item9 ```{r perf-ai-overtime-age-item9} # TikTok result <- create_timeline( data = data, title = "TikTok", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_9", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-overtime-gender-item1} # Google result <- create_timeline( data = data, title = "Google", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_1", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-overtime-gender-item2} # Netflix result <- create_timeline( data = data, title = "Netflix", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_2", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-overtime-gender-item3} # Whatsapp result <- create_timeline( data = data, title = "Whatsapp", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_3", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-overtime-gender-item4} # Facebook result <- create_timeline( data = data, title = "Facebook", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_4", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-overtime-gender-item5} # Bol.com result <- create_timeline( data = data, title = "Bol.com", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_5", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-overtime-gender-item6} # DigID result <- create_timeline( data = data, title = "DigID", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_6", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-overtime-gender-item7} # NOS News result <- create_timeline( data = data, title = "NOS News", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_7", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-overtime-gender-item8} # Albert Heijn result <- create_timeline( data = data, title = "Albert Heijn", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_8", group_var = "geslacht" ) result ``` ###### item9 ```{r perf-ai-overtime-gender-item9} # TikTok result <- create_timeline( data = data, title = "TikTok", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_9", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-ai-overtime-edu-item1} # Google result <- create_timeline( data = data, title = "Google", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_1", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-ai-overtime-edu-item2} # Netflix result <- create_timeline( data = data, title = "Netflix", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_2", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-ai-overtime-edu-item3} # Whatsapp result <- create_timeline( data = data, title = "Whatsapp", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_3", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 4 ```{r perf-ai-overtime-edu-item4} # Facebook result <- create_timeline( data = data, title = "Facebook", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_4", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 5 ```{r perf-ai-overtime-edu-item5} # Bol.com result <- create_timeline( data = data, title = "Bol.com", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_5", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 6 ```{r perf-ai-overtime-edu-item6} # DigID result <- create_timeline( data = data, title = "DigID", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_6", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 7 ```{r perf-ai-overtime-edu-item7} # NOS News result <- create_timeline( data = data, title = "NOS News", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_7", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 8 ```{r perf-ai-overtime-edu-item8} # Albert Heijn result <- create_timeline( data = data, title = "Albert Heijn", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_8", group_var = "Education" ) result ``` ###### item9 ```{r perf-ai-overtime-edu-item9} # TikTok result <- create_timeline( data = data, title = "TikTok", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS2_9", group_var = "Education" ) result ``` ## {{< iconify ph magic-wand-fill >}} Gen AI ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Performance tasks: proportion correct or selected. Where items are multi-select, we show the share selecting each action.", preset = "question") ``` [ {{< iconify ph cards >}} See all Gen AI results ](gen_ai.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-genai-wave1-overall} # Spot non-AI image result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PAIS1R), title = "Spot non-AI image", questions = "PAIS1R", question_labels = "Spot non-AI image", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave1-age-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave1-gender-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave1-edu-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS1R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-genai-wave2-overall} # Spot non-AI image result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PAIS1R), title = "Spot non-AI image", questions = "PAIS1R", question_labels = "Spot non-AI image", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave2-age-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PAIS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave2-gender-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PAIS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-wave2-edu-item1} # Spot non-AI image result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PAIS1R), title = "Spot non-AI image", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PAIS1R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-overtime-overall-item1} # Spot non-AI image result <- create_timeline( data = data, title = "Spot non-AI image", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PAIS1R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-overtime-age-item1} # Spot non-AI image result <- create_timeline( data = data, title = "Spot non-AI image", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS1R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-overtime-gender-item1} # Spot non-AI image result <- create_timeline( data = data, title = "Spot non-AI image", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS1R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-genai-overtime-edu-item1} # Spot non-AI image result <- create_timeline( data = data, title = "Spot non-AI image", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PAIS1R", group_var = "Education" ) result ``` ```{=html} <nav class='pagination-nav' role='navigation' aria-label='Page navigation'> <div class='pagination-container'> <a href='performance_p2.html' class='pagination-btn pagination-prev' aria-label='Previous page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M12 16L6 10L12 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </a> <div class='pagination-info'> <input type='number' class='pagination-input' id='page-input' min='1' max='3' value='3' aria-label='Current page'> <span class='pagination-separator'>/ 3</span> </div> <button class='pagination-btn pagination-next pagination-disabled' disabled aria-label='Next page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M8 16L14 10L8 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </button> </div> </nav> <!-- Pagination Navigation Script --> <script> (function() { const pageUrls = ["performance.html","performance_p2.html","performance_p3.html"]; const pageInput = document.getElementById('page-input'); if (pageInput) { pageInput.addEventListener('change', function() { const pageNum = parseInt(this.value); if (pageNum >= 1 && pageNum <= pageUrls.length) { window.location.href = pageUrls[pageNum - 1]; } else { this.value = this.getAttribute('value'); } }); pageInput.addEventListener('keypress', function(e) { if (e.key === 'Enter') { this.blur(); } }); } })(); </script> ``` ```{=html} <style> /* Ultra-Minimal Pagination Navigation */ .pagination-nav { position: sticky; bottom: 2rem; margin: 3rem auto 2rem auto; max-width: 240px; z-index: 100; } .pagination-container { display: flex; align-items: center; justify-content: center; gap: 1rem; padding: 0.5rem 1rem; background: transparent; } .pagination-btn { display: flex; align-items: center; justify-content: center; width: 32px; height: 32px; padding: 0; background: transparent; color: var(--bs-secondary, #6c757d); text-decoration: none; border-radius: 0.375rem; transition: all 0.15s ease; border: none; cursor: pointer; } .pagination-btn:hover:not(.pagination-disabled) { background: var(--bs-light, #f8f9fa); color: var(--bs-body-color, #212529); } .pagination-btn:active:not(.pagination-disabled) { background: var(--bs-gray-200, #e9ecef); } .pagination-btn.pagination-disabled { color: var(--bs-gray-300, #dee2e6); cursor: default; } .pagination-icon { flex-shrink: 0; opacity: 0.7; } .pagination-btn:hover:not(.pagination-disabled) .pagination-icon { opacity: 1; } .pagination-info { display: flex; align-items: center; gap: 0.5rem; font-size: 0.875rem; color: var(--bs-secondary, #6c757d); } .pagination-input { width: 2.5rem; padding: 0.25rem 0.5rem; text-align: center; border: 1px solid transparent; border-radius: 0.25rem; font-size: 0.875rem; font-weight: 500; color: var(--bs-body-color, #212529); background: transparent; transition: all 0.15s ease; } .pagination-input:hover { background: var(--bs-light, #f8f9fa); border-color: var(--bs-border-color, #dee2e6); } .pagination-input:focus { outline: none; background: var(--bs-body-bg, #fff); border-color: var(--bs-primary, #0d6efd); box-shadow: 0 0 0 2px rgba(13, 110, 253, 0.1); } .pagination-input::-webkit-inner-spin-button, .pagination-input::-webkit-outer-spin-button { opacity: 0; } .pagination-separator { color: var(--bs-secondary, #6c757d); font-weight: 400; font-size: 0.875rem; } /* Responsive */ @media (max-width: 768px) { .pagination-nav { max-width: 220px; bottom: 1.5rem; } .pagination-container { gap: 0.75rem; padding: 0.4rem 0.75rem; } .pagination-btn { width: 30px; height: 30px; } .pagination-icon { width: 16px; height: 16px; } .pagination-info { font-size: 0.8rem; } .pagination-input { width: 2.25rem; font-size: 0.8rem; } } @media (max-width: 480px) { .pagination-nav { max-width: 200px; } .pagination-btn { width: 28px; height: 28px; } } /* Dark mode support */ @media (prefers-color-scheme: dark) { .pagination-btn:hover:not(.pagination-disabled) { background: rgba(255, 255, 255, 0.05); } .pagination-btn:active:not(.pagination-disabled) { background: rgba(255, 255, 255, 0.1); } .pagination-input:hover { background: rgba(255, 255, 255, 0.05); } } /* Override Quarto's back-to-top button position */ .back-to-top { right: 2rem !important; left: auto !important; } @media (max-width: 768px) { .back-to-top { right: 1rem !important; } } </style> ``` 